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Hadoop > Learn Hadoop > Will Spark overtake Hadoop? Will Hadoop be replaced...
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Will Spark overtake Hadoop? Will Hadoop be replaced by Spark?

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"Transforming your struggles into success"

Spark can never be a replacement for Hadoop! Spark is a processing engine on top of Hadoop ecosystem.
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My teaching experience 12 years

Spark can never be a replacement for Hadoop! Spark is a processing engine on top of Hadoop ecosystem.
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"Rajesh Kumar N: Guiding Young Minds from 1 to 12 with Expertise and Care"

Spark and Hadoop serve different purposes, and while Spark has gained popularity for certain use cases, it's unlikely to completely replace Hadoop. Here’s a breakdown: ### 1. **Different Strengths**: - **Hadoop**: Best for batch processing large datasets and is great for data storage with HDFS. ...
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Spark and Hadoop serve different purposes, and while Spark has gained popularity for certain use cases, it's unlikely to completely replace Hadoop. Here’s a breakdown: ### 1. **Different Strengths**: - **Hadoop**: Best for batch processing large datasets and is great for data storage with HDFS. - **Spark**: Excels in in-memory processing, which makes it faster for iterative algorithms and real-time data processing. ### 2. **Complementary Use**: - Many organizations use both Hadoop and Spark together. Hadoop can be used for data storage (HDFS), while Spark can handle data processing tasks. ### 3. **Adoption Trends**: - Spark’s ease of use and speed has led to increased adoption for real-time analytics and machine learning, which may lead to a decline in Hadoop's exclusive use for these tasks. ### 4. **Future Outlook**: - Instead of a replacement, it's more likely that Spark will continue to coexist with Hadoop, enhancing its capabilities, especially in data processing. ### Summary: Spark may not replace Hadoop entirely but will likely continue to gain traction, especially for real-time and iterative processing tasks, while Hadoop remains relevant for large-scale batch processing and storage. read less
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